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3D palmprint recognition using complete block wise descriptor

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Abstract

Recent years have witnessed a growing interesting in developing automatic 3D palmprint recognition systems. The key problem of 3D palmprint recognition is to contrive an effective representation. In this paper, we propose a 3D palmprint recognition method by completely fusing of multiple block wise features. First, we propose a shape index multi-direction binary code strategy to extract 2D texture-level features of 3D palmprint. Then, we use the compact surface type binary code scheme to characterize 3D structure-level features of 3D palmprint. Finally, we integrate them together to construct the complete block wise descriptor for 3D palmprint recognition. Experiments conducted on the public available 3D palmprint database validate the effectiveness of our proposed method.

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Acknowledgments

Our special thanks go to Professor Wanzeng Kong for his participating in the revised version.

This work was supported by the National Natural Science Foundation of China (61402143), National Natural Science Foundation of China (U1909202) and Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province (2020E10010).

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Bing Yang and Xueqin Xiang prepared the manuscript, Duanqing Xu provided new ideas about 3D palmprint recognition, Jinliang Yao focused on algorithm implementation. All authors read and approved the manuscript.

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Correspondence to Bing Yang.

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The authors declare that they have no competing financial interests.

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Yang, B., Xiang, X., Yao, J. et al. 3D palmprint recognition using complete block wise descriptor. Multimed Tools Appl 79, 21987–22006 (2020). https://doi.org/10.1007/s11042-020-09000-7

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  • DOI: https://doi.org/10.1007/s11042-020-09000-7

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